CASIA OpenIR
Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging
Chen, Shuling1; Feng, Shiting2; Wei, Jingwei3,4,5; Liu, Fei3,4,5; Li, Bin6; Li, Xin7; Hou, Yang8; Gu, Dongsheng3,4,5; Tang, Mimi9; Xiao, Han9; Jia, Yingmei2; Peng, Sui6,9; Tian, Jie3,4,5; Kuang, Ming1,10
Source PublicationEUROPEAN RADIOLOGY
ISSN0938-7994
2019-08-01
Volume29Issue:8Pages:4177-4187
Corresponding AuthorTian, Jie(tian@ieee.org) ; Kuang, Ming(kuangminda@hotmail.com)
AbstractObjectivesImmunoscore evaluates the density of CD3+ and CD8+ T cells in both the tumor core and invasive margin. Pretreatment prediction of immunoscore in hepatocellular cancer (HCC) is important for precision immunotherapy. We aimed to develop a radiomics model based on gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA)-enhanced MRI for pretreatment prediction of immunoscore (0-2 vs. 3-4) in HCC.Materials and methodsThe study included 207 (training cohort: n=150; validation cohort: n=57) HCC patients with hepatectomy who underwent preoperative Gd-EOB-DTPA-enhanced MRI. The volumes of interest enclosing hepatic lesions including intratumoral and peritumoral regions were manually delineated in the hepatobiliary phase of MRI images, from which 1044 quantitative features were extracted and analyzed. Extremely randomized tree method was used to select radiomics features for building radiomics model. Predicting performance in immunoscore was compared among three models: (1) using only intratumoral radiomics features (intratumoral radiomics model); (2) using combined intratumoral and peritumoral radiomics features (combined radiomics model); (3) using clinical data and selected combined radiomics features (combined radiomics-based clinical model).ResultsThe combined radiomics model showed a better predicting performance in immunoscore than intratumoral radiomics model (AUC, 0.904 (95% CI 0.855-0.953) vs. 0.823 (95% CI 0.747-0.899)). The combined radiomics-based clinical model showed an improvement over the combined radiomics model in predicting immunoscore (AUC, 0926 (95% CI 0884-0967) vs. 0904 (95% CI 0855-0953)), although differences were not statistically significant. Results were confirmed in validation cohort and calibration curves showed good agreement.ConclusionThe MRI-based combined radiomics nomogram is effective in predicting immunoscore in HCC and may help making treatment decisions.Key Points center dot Radiomics obtained from Gd-EOB-DTPA-enhanced MRI help predicting immunoscore in hepatocellular carcinoma.center dot Combined intratumoral and peritumoral radiomics are superior to intratumoral radiomics only in predicting immunoscore.center dot We developed a combined clinical and radiomicsnomogram to predict immunoscore in hepatocellular carcinoma.
KeywordCarcinoma Hepatocellular Gadolinium ethoxybenzyl DTPA Magnetic resonance imaging Immunotherapy
DOI10.1007/s00330-018-5986-x
WOS KeywordTUMOR-INFILTRATING LYMPHOCYTES ; CD8(+) T-CELLS ; CARCINOMA ; FEATURES ; LEVEL ; CLASSIFICATION ; RECURRENCE ; EXPRESSION ; PATTERNS ; DENSITY
Indexed BySCI
Language英语
Funding ProjectGuangzhou Science and Technology Program key projects[201803010057] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81771908] ; National Natural Science Foundation of China[81571750] ; Ministry of Science and Technology of China[2017YFA0205200] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Beijing Municipal Science & Technology Commission[Z161100002616022] ; Beijing Municipal Science & Technology Commission[Z171100000117023] ; Key International Cooperation Projects of the Chinese Academy of Sciences[173211KYSB20160053]
Funding OrganizationGuangzhou Science and Technology Program key projects ; National Natural Science Foundation of China ; Ministry of Science and Technology of China ; Chinese Academy of Sciences ; Beijing Municipal Science & Technology Commission ; Key International Cooperation Projects of the Chinese Academy of Sciences
WOS Research AreaRadiology, Nuclear Medicine & Medical Imaging
WOS SubjectRadiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000473737100025
PublisherSPRINGER
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26880
Collection中国科学院自动化研究所
Corresponding AuthorTian, Jie; Kuang, Ming
Affiliation1.Sun Yat Sen Univ, Affiliated Hosp 1, Inst Diagnost & Intervent Ultrasound, Dept Med Ultrason, 58 Zhong Shan Rd 2, Guangzhou 510080, Guangdong, Peoples R China
2.Sun Yat Sen Univ, Affiliated Hosp 1, Dept Radiol, 58 Zhong Shan Rd 2, Guangzhou 510080, Guangdong, Peoples R China
3.Chinese Acad Sci, Inst Automat, Key Lab Mol Imaging, Beijing 100190, Peoples R China
4.Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
6.Sun Yat Sen Univ, Affiliated Hosp 1, Clin Trial Unit, 58 Zhong Shan Rd 2, Guangzhou 510080, Guangdong, Peoples R China
7.GE HealthCare China, Shanghai 200000, Peoples R China
8.Jinan Univ, Dept Math, Guangzhou 510632, Guangdong, Peoples R China
9.Sun Yat Sen Univ, Affiliated Hosp 1, Dept Gastroenterol & Hepatol, 58 Zhong Shan Rd 2, Guangzhou 510080, Guangdong, Peoples R China
10.Sun Yat Sen Univ, Affiliated Hosp 1, Dept Liver Surg, 58 Zhong Shan Rd 2, Guangzhou 510080, Guangdong, Peoples R China
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences;  Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Chen, Shuling,Feng, Shiting,Wei, Jingwei,et al. Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging[J]. EUROPEAN RADIOLOGY,2019,29(8):4177-4187.
APA Chen, Shuling.,Feng, Shiting.,Wei, Jingwei.,Liu, Fei.,Li, Bin.,...&Kuang, Ming.(2019).Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging.EUROPEAN RADIOLOGY,29(8),4177-4187.
MLA Chen, Shuling,et al."Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging".EUROPEAN RADIOLOGY 29.8(2019):4177-4187.
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